Tizzani Michele, Gauvin Laetitia
ISI Foundation, Turin, Italy.
Department of Applied Mathematics and Computer Science, Technical University of Denmark, Copenhagen, Denmark.
PLoS Comput Biol. 2025 Aug 4;21(8):e1013262. doi: 10.1371/journal.pcbi.1013262. eCollection 2025 Aug.
Socioeconomic inequalities significantly influence infectious disease outcomes, as seen with COVID-19, but the pathways through which socioeconomic conditions affect transmission dynamics remain unclear. To address this, we conducted a survey representative of the Italian population, stratified by age, gender, geographical area, city size, employment status, and education level. The survey's final aim was to estimate differences in contact and protective behaviors across various population strata, both of which are crucial for understanding transmission dynamics. Our initial insights based on the survey indicate that years after the pandemic began, the perceived impact of COVID-19 on professional, economic, social, and psychological dimensions vary across socioeconomic strata, extending beyond the epidemiological outcomes. This reinforces the need for approaches that systematically consider socioeconomic determinants. In this context, using generalized linear models, we identified associations between socioeconomic factors and vaccination status for both COVID-19 and influenza, as well as the influence of socioeconomic conditions on mask-wearing and social distancing. Importantly, we also observed differences in contact behaviors based on employment status while education level did not show a significant association. These findings highlight the complex interplay of socioeconomic and demographic factors in shaping protective behavior and contact patterns. Understanding these dynamics can contribute to the improvement of epidemic models and better guide public health efforts for at-risk groups.
社会经济不平等对传染病的结果有显著影响，如在新冠疫情中所见，但社会经济状况影响传播动态的途径仍不清楚。为了解决这一问题，我们进行了一项具有意大利人口代表性的调查，按年龄、性别、地理区域、城市规模、就业状况和教育水平进行分层。该调查的最终目的是估计不同人群阶层在接触行为和防护行为上的差异，这两者对于理解传播动态都至关重要。我们基于该调查的初步见解表明，在疫情开始多年后，新冠疫情对职业、经济、社会和心理层面的感知影响在不同社会经济阶层中有所不同，这超出了流行病学结果的范畴。这强化了采用系统考虑社会经济决定因素的方法的必要性。在此背景下，我们使用广义线性模型，确定了社会经济因素与新冠疫苗和流感疫苗接种状况之间的关联，以及社会经济状况对佩戴口罩和保持社交距离的影响。重要的是，我们还观察到基于就业状况的接触行为差异，而教育水平并未显示出显著关联。这些发现凸显了社会经济和人口因素在塑造防护行为和接触模式方面的复杂相互作用。了解这些动态有助于改进疫情模型，并更好地指导针对高危人群的公共卫生工作。
